List of clustered permutations in secondary memory for proximity searching

Autores
Roggero, Patricia; Reyes, Nora Susana; Figueroa, Karina; Paredes, Rodrigo
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Similarity search is a difficult problem and various indexing schemas have been defined to process similarity queries efficiently in many applications, including multimedia databases and other repositories handling complex objects. Metric indices support efficient similarity searches, but most of them are designed for main memory. Thus, they can handle only small datasets, suffering serious performance degradations when the objects reside on disk. Most reallife database applications require indices able to work on secondary memory. Among a plethora of indices, the List of Clustered Permutations (LCP) has shown to be competitive in main memory.We introduce a secondary-memory variant of the LCP, which maintains the low number of distance evaluations when comparing the permutations themselves, and also needs a low number of I/O operations at construction and searching.
Facultad de Informática
Materia
Ciencias Informáticas
metric spaces
permutation-based algorithm
list of clusters
secondary memory
Search process
Secondary storage
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/50184
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/50184
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling List of clustered permutations in secondary memory for proximity searchingRoggero, PatriciaReyes, Nora SusanaFigueroa, KarinaParedes, RodrigoCiencias Informáticasmetric spacespermutation-based algorithmlist of clusterssecondary memorySearch processSecondary storageSimilarity search is a difficult problem and various indexing schemas have been defined to process similarity queries efficiently in many applications, including multimedia databases and other repositories handling complex objects. Metric indices support efficient similarity searches, but most of them are designed for main memory. Thus, they can handle only small datasets, suffering serious performance degradations when the objects reside on disk. Most reallife database applications require indices able to work on secondary memory. Among a plethora of indices, the List of Clustered Permutations (LCP) has shown to be competitive in main memory.We introduce a secondary-memory variant of the LCP, which maintains the low number of distance evaluations when comparing the permutations themselves, and also needs a low number of I/O operations at construction and searching.Facultad de Informática2015-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf107-113http://sedici.unlp.edu.ar/handle/10915/50184enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST41-Paper-10.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:45:20Zoai:sedici.unlp.edu.ar:10915/50184Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:45:21.122SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv List of clustered permutations in secondary memory for proximity searching
title List of clustered permutations in secondary memory for proximity searching
spellingShingle List of clustered permutations in secondary memory for proximity searching
Roggero, Patricia
Ciencias Informáticas
metric spaces
permutation-based algorithm
list of clusters
secondary memory
Search process
Secondary storage
title_short List of clustered permutations in secondary memory for proximity searching
title_full List of clustered permutations in secondary memory for proximity searching
title_fullStr List of clustered permutations in secondary memory for proximity searching
title_full_unstemmed List of clustered permutations in secondary memory for proximity searching
title_sort List of clustered permutations in secondary memory for proximity searching
dc.creator.none.fl_str_mv Roggero, Patricia
Reyes, Nora Susana
Figueroa, Karina
Paredes, Rodrigo
author Roggero, Patricia
author_facet Roggero, Patricia
Reyes, Nora Susana
Figueroa, Karina
Paredes, Rodrigo
author_role author
author2 Reyes, Nora Susana
Figueroa, Karina
Paredes, Rodrigo
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
metric spaces
permutation-based algorithm
list of clusters
secondary memory
Search process
Secondary storage
topic Ciencias Informáticas
metric spaces
permutation-based algorithm
list of clusters
secondary memory
Search process
Secondary storage
dc.description.none.fl_txt_mv Similarity search is a difficult problem and various indexing schemas have been defined to process similarity queries efficiently in many applications, including multimedia databases and other repositories handling complex objects. Metric indices support efficient similarity searches, but most of them are designed for main memory. Thus, they can handle only small datasets, suffering serious performance degradations when the objects reside on disk. Most reallife database applications require indices able to work on secondary memory. Among a plethora of indices, the List of Clustered Permutations (LCP) has shown to be competitive in main memory.We introduce a secondary-memory variant of the LCP, which maintains the low number of distance evaluations when comparing the permutations themselves, and also needs a low number of I/O operations at construction and searching.
Facultad de Informática
description Similarity search is a difficult problem and various indexing schemas have been defined to process similarity queries efficiently in many applications, including multimedia databases and other repositories handling complex objects. Metric indices support efficient similarity searches, but most of them are designed for main memory. Thus, they can handle only small datasets, suffering serious performance degradations when the objects reside on disk. Most reallife database applications require indices able to work on secondary memory. Among a plethora of indices, the List of Clustered Permutations (LCP) has shown to be competitive in main memory.We introduce a secondary-memory variant of the LCP, which maintains the low number of distance evaluations when comparing the permutations themselves, and also needs a low number of I/O operations at construction and searching.
publishDate 2015
dc.date.none.fl_str_mv 2015-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/50184
url http://sedici.unlp.edu.ar/handle/10915/50184
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST41-Paper-10.pdf
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
dc.format.none.fl_str_mv application/pdf
107-113
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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